• 한국생물공학회:학술대회논문집
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• 2000.11a
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• pp.709-710
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• 2000

Genosensor technology utilizes a patterned array of DNA molecules immobilized on solid supports for biomedical analysis. The detection capability of the sensor depended mainly on the way the capture probes are attached to the support as well as the sequence. We compared two different. coupling methods currently used to covalently graft DNA molecules onto a glass surface.

• Journal of Ginseng Research
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• v.35 no.1
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• pp.111-123
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• 2011

To investigate the effects of repeated immobilization-stress challenge on the the hypothalamic-pituitary-adrenal axis, the genomic transcriptome in the adrenal cortex of immobilization-stressed mouse was analyzed by using a cDNA microarray. Mice were subjected to immobilization stress for 2 h per day for 5 consecutive d. With a 4.0-fold cutoff of arbitrary criteria, the expression levels of 168 out of 41,174 genes were significantly modulated in the adrenal cortex by stress when comparing the control and experimental groups. These genes were related to apoptosis, cell cycle, immune response, inflammatory responses, and signal transduction, and thus may be used as potential targets for the development of therapeutics for chronic stress or depression. Six significant genes among these were selected for real time polymerase chain reaction analysis to confirm the change of their expression levels. The gene for phospho 1 was also further investigated because its expression showed the greatest fold-change.

• Genomics & Informatics
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• v.11 no.4
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• pp.180-185
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• 2013

Development of liver cancers is driven largely by genomic alterations that deregulate signaling pathways, influencing growth and survival of cancer cells. Because of the hundreds or thousands of genomic/epigenomic alterations that have accumulated in the cancer genome, it is very challenging to find and test candidate genes driving tumor development and progression. Systematic studies of the liver cancer genome have become available in recent years. These studies have uncovered new potential driver genes, including those not previously known to be involved in the development of liver cancer. Novel approaches combining multiple datasets from patient tissues have created an unparalleled opportunity to uncover potential new therapeutic targets and prognostic/predictive biomarkers for personalized therapy that can improve clinical outcomes of the patients with liver cancer.